How to use Phora68/rapha with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Phora68/rapha:Q4_K_M # Run inference directly in the terminal: llama cli -hf Phora68/rapha:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Phora68/rapha:Q4_K_M # Run inference directly in the terminal: llama cli -hf Phora68/rapha:Q4_K_M
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Phora68/rapha:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Phora68/rapha:Q4_K_M
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Phora68/rapha:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Phora68/rapha:Q4_K_M
docker model run hf.co/Phora68/rapha:Q4_K_M
How to use Phora68/rapha with Ollama:
ollama run hf.co/Phora68/rapha:Q4_K_M
How to use Phora68/rapha with Docker Model Runner:
How to use Phora68/rapha with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Phora68/rapha:Q4_K_M
lemonade run user.rapha-Q4_K_M
lemonade list
